Quantum Computer Can Teach Itself Everything - Scientist

The National University of Science and Technology MISiS (NUST MISiS) is enrolling students in its new iPHD program Quantum Materials Science and an MA program called Quantum Technologies of Materials and Devices.

Professor George Tsironis from Greece, a famous scientist dealing with machine learning in quantum physics and materials science, discusses his own module for both programs.

Sputnik: How can students benefit from the iPHD program?

George Tsironis: It is very important that students are just not left to themselves, but that they take part in collaborations with foreign universities, international scientists and students from other countries. This program provides excellent opportunities for such mobility between research groups.

One advantage of the program is that, instead of enrolling in a particular course, a student teams up with a certain head of research. He or she receives a grant and starts working at laboratories while earning an MA degree; the student later completes a postgraduate course and continues to study and carry out research. In fact, we determine the path a person takes to becoming a scientist and minimize the gap between science and education.

The modular program allows students to study and undergo advanced training all over the world. In total, 18 people with BA degrees who are fascinated by quantum materials science have already enrolled.

Sputnik: What is the gist of your course Machine Learning of Complicated Systems and Quantum Matter?

George Tsironis: This is the first such course. Actually, as of now, there is no other course on machine learning of quantum materials science anywhere in the world. Machine Learning is becoming topical because experts are looking for new data-handling methods in all research fields. This course deals precisely with Big Data Science and Machine Learning. It quickly introduces students to Big Data Science, so that they will be able to start handling big data and use it in their research.

Sputnik: What lies in store for these students? Where will they work?

George Tsironis: The program’s graduates will be able to continue their careers as postdoctoral research fellows at leading universities worldwide and as research associates with academic organizations or as staffers at research and development (R&D) companies. Most important, they need to study constantly in order to become good scientists and specialists.

All aspects of the course are linked with artificial intelligence. Consequently, this knowledge can be used in any field, including self-controlling machines, machine translation, etc. For example, physicists use this knowledge to make calculations and create simulations. People have to work with big data everywhere, and new approaches are also needed in every area. This is where the future begins. Scientists handling big data volumes are among the most popular careers in the United States.

To my mind, modern students are sufficiently qualified and boast a quite impressive level of preliminary knowledge. They successfully cope with the tasks that I set, which are not that easy.

Sputnik: What’s so difficult about them? How can Machine Learning contribute to the development of quantum physics?

George Tsironis: One of the aspects of quantum physics is quantum computer qubits. This is exactly what we are dealing with. It is necessary to sort out big data volumes, utilize and fine-tune ties between several qubits. This is where Machine Learning comes into play.

Qubits and quantum computers are already being developed. But a new mathematics that is completely different from ordinary mathematics is emerging as well. Machine Learning will make it possible to work with such mathematical methods, to create new algorithms and tasks, to control the quantum computer and Big Data flows at an entirely new level.

Machine Learning will make it possible to create a self-teaching quantum computer. Just imagine, it will be confronted with a problem, but it will independently find and select the required data, teach itself and solve this particular problem. An ordinary computer and a computer with Machine Learning interface have different principles of operation. We tell the ordinary computer what it should do; we program the computer, and it accomplishes a certain task. But in the case of a computer with a Machine Learning interface, we set it a task so that it learns something new.

Sputnik: Has science come close to creating a self-teaching quantum computer? What is your forecast?

George Tsironis: Speaking of the quantum computer’s future, it is still too early to make any forecasts. These computers are only just coming to the fore, and they are not very effective yet. But we should understand that the quantum computer will be able to independently master quantum physics in the future. This will be a unique machine.

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